class_docstr: A wrapper converting MultiAgentEnv from old gym API to the new one.
  
  "Old API" refers to step() method returning (observation, reward, done, info),
  and reset() only retuning the observation.
  "New API" refers to step() method returning (observation, reward, terminated,
  truncated, info) and reset() returning (observation, info).
  
  Known limitations:
  - Environments that use `self.np_random` might not work as expected.
docstr: A wrapper which converts old-style envs to valid modern envs.
  
  Some information may be lost in the conversion, so we recommend updating your
  environment.
  
  Args:
      old_env: The old MultiAgentEnv to wrap. Implemented with the old API.
      render_mode: The render mode to use when rendering the environment,
          passed automatically to `env.render()`.
docstr_tok: ["A","wrapper","which","converts","old-style","envs","to","valid","modern","envs",".","Some","information","may","be","lost","in","the","conversion",",","so","we","recommend","updating","your","environment",".","Args",":","old_env",":","The","old","MultiAgentEnv","to","wrap",".","Implemented","with","the","old","API",".","render_mode",":","The","render","mode","to","use","when","rendering","the","environment",",","passed","automatically","to","`","env.render","(",")","`","."]
code: def __init__(self, old_env, render_mode: Optional[str] = None):
      """A wrapper which converts old-style envs to valid modern envs.
  
      Some information may be lost in the conversion, so we recommend updating your
      environment.
  
      Args:
          old_env: The old MultiAgentEnv to wrap. Implemented with the old API.
          render_mode: The render mode to use when rendering the environment,
              passed automatically to `env.render()`.
      """
      super().__init__()
  
      self.metadata = getattr(old_env, "metadata", {"render_modes": []})
      self.render_mode = render_mode
      self.reward_range = getattr(old_env, "reward_range", None)
      self.spec = getattr(old_env, "spec", None)
      self.env = old_env
  
      self.observation_space = old_env.observation_space
      self.action_space = old_env.action_space
  
file_path: ray/rllib/env/wrappers/multi_agent_env_compatibility.py
imports: from typing import Optional, Tuple
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.utils.typing import MultiAgentDict
label_desc: Use image node_id 1 to create a new MultiAgentEnvCompatibility object from inherited base classes: MultiAgentEnv with example: obj = MultiAgentEnvCompatibility(old_env, render_mode)